Abstract

Social network graphs are often used to help inform judgments in a
variety of domains, such as public health, law enforcement, and political
science. Across two studies, we examined how graph features influenced
probabilistic judgments in graph-based social network analysis and identified
multiple heuristics that participants used to inform these judgments. Study 1
demonstrated that participants’ judgments were influenced by information
about direct connections, base rates, and layout proximity, and
participants’ self-reported strategies also reflected use of this
information. Study 2 replicated findings from Study 1 and provided additional
insight into the hierarchical ordering of these strategies and the decision
process underlying judgments from social network graphs.